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broking industry: What technology charged up stock broking in the year of Robinhoods

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Digitization of the broking industry has brought technology-based benefits to investors, who are increasingly looking for easy-to-use, secure and hassle-free trading platforms. The digital transformation of the Indian broking industry accelerated in 2020.

During the lockdown, more and more people turned to trading on online brokerage platforms. To cater to this unprecedented trading volume and deliver enhanced trading experiences, brokers adopted innovative technologies such as cloud-based systems and IT-enabled applications that form the broking industry’s backbone.

Brokers are increasingly migrating to cloud-based systems to meet the spike in trading volumes and new account openings. Unlike legacy infrastructure, cloud computing offers easy scalability, cost-effective and time-saving services, and a level of flexibility never seen before in the sector.

The result? Today, one can enjoy high-value trading seamlessly, even on a smartphone. Technology has emerged as a critical differentiator in a highly-competitive market that helps brokers continuously create value for investors.

Let’s deep-dive into the critical technology applications that helped brokerages stay competitive during the ongoing Covid-19 crisis:

Business on cloud

A game-changer in technology, cloud-computing relieved brokers from infrastructure management hassles, allowing them to focus on the server-side code. This facilitates easy code deployment at reduced costs by DevOps teams. They also offer the benefit of dynamic and real-time auto-scaling. This is essential to serve a growing customer base but lacks traditional legacy infrastructures with fixed server spaces.

Cloud architectures are designed to help companies accommodate growing service requests without worrying about provisioning needs. They are unlike legacy servers, where developers estimate and buy server capacity without knowing how much they will ultimately use or require later.

Besides scalability, cloud architectures offer the flexibility to ‘pay as you go’; and allow businesses to get charged for only what is used, unlike traditional servers, which need to be 24×7 operational. The result? Greater efficiency at reduced cost and without wastage of server space.

Data lake and analytics platforms

The data-rich stockbroking industry needs to leverage data and derive real-time insights to make critical strategic decisions. Data lakes can function as a secure, one-stop-shop for different types of data from diverse sources, stored in raw or their native format, in fully structured, semi-structured, and unstructured manners. With data lakes, brokers can gather useful data and enjoy real-time analytics to uncover critical, relevant insights for faster and more improved decision-making.

The same data lake allows different types of analytics to be run without needing separate systems. For instance, trading desks can leverage data to achieve a number of specific objectives, such as figuring out which stocks have an abnormal spike in volume. Real-time statistical analysis allows traders to make more informed decisions.

Predictive modeling capabilities

Outstanding customer experience is going to be the most significant competitive advantage for stockbrokers. Using machine-learning algorithms to analyze historical data and predict likely outcomes, brokers can forecast investor needs and proactively offer customised services at better prices.

As more and more savvy investors are using digital assets like websites and mobile apps for trading, predictive modeling can help brokers design a UI that ensures an optimal user experience. For instance, a user-friendly UI empowers the user to assess various options before making a buy/sell call. It can let you know if a stock has been tagged as illiquid, expecting any corporate actions in the near future or any recent news centered around the industry.

Smart machines

Artificial intelligence finds tremendous application in the broking industry. From automating processes to increase efficiency and designing agile, customer-centric solutions, AI helps brokers offer an improved value proposition to investors. By investing in cutting-edge cognitive automation technologies, brokers can reduce paperwork and automate processes, enabling professionals to spend more time in critical decision-making.

AI-powered chatbots can help offer more personalized services, to investors, like stock research, quick and personalized portfolio creation, and addressing customer queries. With an increasingly younger pool of investors, global AI spends are expected to rise 48% CAGR and are projected to reach $1.4 billion by 2021. Clearly, AI-enabled trading will be the new normal.

Enhanced risk management

Stringent adherence to regulatory compliances fosters stakeholder trust. Technology can be a growth enabler in an increasingly-complex compliance and regulatory risk landscape, helping stockbrokers modernise and manage compliance better. Early adopters of the technology will enjoy a competitive advantage over others, as they will be able to offer more accuracy, convenience, and a top-notch customer experience through their services.

From video KYC to the use of natural language processing (NLP) and cognitive automation processes to facilitate client onboarding, digitization offers a host of opportunities for more seamless compliance. Brokers need to invest in AI-ML models and technologies like big data analytics, biometric recognition for predicting risks of frauds, cybersecurity, data breach, and to enforce better compliance in a sector fraught with fraudulent activities.

With the emergence of a digital economy, there has been a rapid change in investor expectations, market trends, and business ecosystems. The only way for stockbrokers to stay ahead of the curve is to redefine existing business models with digital transformation.

(Shrini Viswanath is the Co-founder & CTO of Upstox. Views are his own)

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